{"id":"W2068821930","doi":"10.1007/s11270-014-2045-3","title":"(Methyl)Mercury, Arsenic, and Lead Contamination of the World’s Largest Wastewater Irrigation System: the Mezquital Valley (Hidalgo State—Mexico)","year":2014,"lang":"en","type":"article","venue":"Water Air & Soil Pollution","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; National Research Council Canada","keywords":"Wastewater; Environmental chemistry; Mercury (programming language); Irrigation; Groundwater; Environmental science; Soil water; Arsenic; Surface water; Environmental engineering; Chemistry; Agronomy; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000200077,0.0001205627,0.00008972116,0.0006296959,0.0006139106,0.0004294045,0.0002100683,0.0002779085,0.0009661226],"category_scores_gemma":[0.0003638364,0.0001432636,0.0001499266,0.0007242265,0.0002195406,0.0001833564,0.0004041059,0.0001818882,0.00008085831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007670278,"about_ca_system_score_gemma":0.0007987912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2227482,"about_ca_topic_score_gemma":0.3379344,"domain_scores_codex":[0.9998928,0.00001971198,0.00000883745,0.00002840826,0.00002932807,0.00002094766],"domain_scores_gemma":[0.9998481,0.00002164035,0.00006567439,0.000008434934,0.00004407164,0.00001196727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004209473,0.00009357993,0.9637589,0.00005672793,0.0001337444,0.0001880649,0.001187806,0.0007902621,0.0213134,0.0001781236,0.0008100665,0.01106823],"study_design_scores_gemma":[0.00001050525,0.00009227927,0.9925467,0.000007153187,0.00005949441,0.00006523224,0.0007680246,0.000323292,0.004376951,0.00004610772,0.001699731,0.000004530404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987051,0.00004031906,0.00007244678,0.00004552615,0.000001302871,0.000005169868,0.0004729919,0.000003098259,0.0006540139],"genre_scores_gemma":[0.9979243,0.00007339098,0.000256204,0.00002586078,0.000001956987,0.000008566739,0.0005747769,0.000001818698,0.001133106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2227482,"threshold_uncertainty_score":0.4429034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008422746277755695,"score_gpt":0.2156345177654424,"score_spread":0.2072117714876867,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}